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Workflow Analysis, Scheduling, and Chance Constraint Models in Community Pharmacy Operations

Salman, Hamdy (2019) Workflow Analysis, Scheduling, and Chance Constraint Models in Community Pharmacy Operations. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Community pharmacy networks provide most of the US population's prescribed medication, but not picking up the medication or using it improperly can lead to problems such as medication non-adherence and medication misuse. This research focuses on improving community pharmacy network services by proposing a change in the role pharmacists play in these networks. A key task pharmacists perform which is a critical step in the medication dispensing process is verifying that the medication filled is the one prescribed and that it does not conflict with other medications the patient is taking. This dissertation proposes that pharmacists provide important counseling services (i.e. PDPC services) to patients inside community pharmacies. We discuss how adding PDPC services changes the workflow of a community pharmacy and discuss strategies to overcome obstacles preventing pharmacists from providing PDPC services.
We use a Discrete Event Simulation (DES) model to simulate a local community pharmacy as well as a community pharmacy network to evaluate strategies that can be used to either improve the workflow process internally (internal strategies) or provide an external resource that can be used to provide support to the pharmacy (external strategies). The internal strategies studied are adding a staff member, predicting prescription pick up times, and providing short duration PDPC services in busy hours. The external strategies studied are utilizing a central fill to dispense part of the pharmacy's demand and adding PDPC kiosks to provide PDPC services inside the pharmacy. The effect of each strategy and the extent of its benefits are studied and highlighted in chapters 2 & 3.
The central fill location problem was modeled as a chance constraint stochastic P-median capacitated facility location problem. Three extensions to the location model are added and discussed in detail. Several lower bounds were provided to the problem and an efficient solution method was used to solve the problem. Finally the model was applied to a community pharmacy network in PA in a case study. The results showed that ignoring the highest demand scenarios can save the community pharmacy network from having to add an additional central fill.


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Item Type: University of Pittsburgh ETD
Status: Unpublished
CreatorsEmailPitt UsernameORCID
Salman, Hamdyhgs6@pitt.eduHGS6HGS6
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee MemberNorman,
Committee MemberZeng,
Committee MemberAbraham,
Committee ChairRajgopal,
Date: 11 September 2019
Date Type: Publication
Defense Date: 6 May 2018
Approval Date: 11 September 2019
Submission Date: 23 April 2019
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Number of Pages: 111
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Industrial Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: Community pharmacy operations
Date Deposited: 11 Sep 2019 14:52
Last Modified: 11 Sep 2019 14:52


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